QuickStats: Percentage of Uninsured Adults Aged 18−64 Years, by Race, Hispanic Origin, and Selected Asian Subgroups — National Health Interview Survey, United States, 2019−2020

July 15, 2022

During 2019–2020, the percentage of U.S. adults aged 18–64 years who were uninsured was 14.4%.

Among all race and Hispanic origin groups, non-Hispanic Asian adults (7.8%) were the least likely to be uninsured followed by non-Hispanic White (9.7%), non-Hispanic Black (14.6%), and Hispanic adults (30.4%).

Among the non-Hispanic Asian subgroups shown, adults of Korean (14.3%) origin were more likely to be uninsured than adults of Asian Indian (4.8%) and Chinese (6.5%) origin.

Other observed differences were not statistically significant.

Source: National Health Interview Survey, 2019 and 2020 data. https://www.cdc.gov/nchs/nhis.htm

QuickStats: Percentage of Uninsured Adults Aged 18–64 Years, by Race and Selected Hispanic Origin Subgroup — National Health Interview Survey, United States, 2019−2020

June 24, 2022

During 2019–2020, the percentage of U.S. adults aged 18–64 years who were uninsured was 14.4%.

Among all race and Hispanic origin subgroups, those most likely to be uninsured were Hispanic adults (30.4%) followed by non-Hispanic Black (14.6%), non-Hispanic White (9.7%), and non-Hispanic Asian (7.8%) adults.

Among the Hispanic origin subgroups included, those most likely to be uninsured were of Central American (42.2%) origin followed by Mexican or Chicano (33.6%) origin.

Adults of Cuban (22.7%) origin were more likely to be uninsured than those of Puerto Rican (14.8%) and Dominican (12.9%) origin. Other observed differences were not statistically significant.

Source: National Center for Health Statistics, National Health Interview Survey, 2019 and 2020. https://www.cdc.gov/nchs/nhis.htm


PODCAST – Q & A on 2020 Maternal Mortality Data

February 23, 2022


HOST: NCHS kicked off the month of February with the latest annual report on Births in the country, using final data from 2020.  Most of the data were already reported in the provisional 2020 report last May, but there are a few topics that did not appear in that report.

For example, cigarette smoking during pregnancy.  The new report shows nearly 6% of women smoked at some point during their pregnancy in 2020, which was an 8% decline from 2019.  Multiple births in the country have dropped as well.  The twin birth rate in 2020 was down 8% from its high in 2014, and the triplet and higher order multiple birth rate was down 9% from 2019.

NCHS also updated its state-by-state life tables, using data from 2019.  The report showed Hawaii and California had the highest life expectancy of any state.  Hawaiians and Californians are expected to live nearly 81 years, according to the 2019 data.  Mississippi had the lowest life expectancy of any state – 74.4 years at birth.

Two new reports using National Health Interview Survey data from 2020 looked at variations in Health Insurance coverage by geographic and demographic factors.  The studies focused on adults between ages 18 and 64.  The geographic study showed that four states – Georgia, Florida, Texas and North Carolina – had uninsured rates among adults that were higher than the national average.  This report also showed that another four states – New York, Pennsylvania, Michigan, and California – had uninsured rates among adults that were lower than the national average.

Meanwhile, in the demographic report, the data show that nearly 1 in 10 or 31.6 million people of all ages were uninsured at the time of the interview. This includes 31.2 million people under age 65. Five percent of children under 18 were uninsured, and 14% of working-age adults ages 18–64. Nearly 2/3 of people under age 65 were covered by private health insurance, and over half were covered from employment-based coverage.   Four percent were covered by exchange-based coverage, a type of directly purchased coverage. Among people under age 65, about 2 out of 5 children and 1 out of 5 adults were covered by public health coverage, mainly by Medicaid and the Children’s Health Insurance Program or “CHIP.”

In other NCHS news, the February release of provisional data on drug overdose deaths in America featured improvements in the timeliness of the data.  Since the monthly releases began in September of 2017, there has been a lag of six months in the data.  However, beginning with the February 2022 release, that lag has been tightened to only four months, so this new release features data from the one-year period ending in September 2021.  The trends, however, remain the same; drug overdose deaths in the U.S. continue to rise, driven by overdoses from fentanyl and other synthetic opioids.

NCHS also updated its marriage and divorce rate tables in February.  Though NCHS hasn’t collected comprehensive statistics on marriage and divorce since the 1990’s, the Center does post annual tables both nationally and by state on the number of marriages and divorces per 1,000 population.  As in years past, Nevada had the highest marriage rate in the nation, more than twice the rate of the next highest state, Montana.  Wyoming had the highest divorce rate per 1,000 in the country, edging out Alabama.

NCHS also has a new report coming out this week showing that 1 in 10 children under age 18 live in households that had food insecurity in the past month, using data from the 2019-2020 National Health Interview Survey.  Non-Hispanic Black children and Hispanic children were more than twice as likely as non-Hispanic white children to live in households experiencing food insecurity in the past month.

Finally, NCHS released new 2020 data on maternal mortality in the U.S.  The new data show that in 2020, 861 women in the United States died of maternal causes, compared with 754 deaths in 2019.  The maternal mortality rate for 2020 was 23.8 deaths per 100,000 live births, compared with a rate of 20.1 in 2019.  The rate for non-Hispanic black women was significantly higher than for Hispanic women and non-Hispanic white women.

For several years, NCHS had paused its collection of maternal mortality statistics due to data quality issues, but the Center resumed collection of these important data in 2018, and the first data in (11 years) were released in January 2020.  At that time we had a Statcast discussion with Robert Anderson, the chief of Mortality Statistics at NCHS about the data quality issues in the past, as well as the new collection efforts.  Here is a snippet of that conversation:


HOST: Now, with maternal mortality there’s a whole back story – can you share that with us?

ROBERT ANDERSON: Yeah, it’s sort of a long and involved process that we’ve gone through over the last decade and a half or so.  So in the past, as we’ve collected data on maternal deaths – and here we’re talking about years prior to 2003 in particular – research had shown that we tended to underestimate maternal deaths.  And so in order to address that issue, we felt that adding a checkbox item to the death certificate asking whether the decedent was pregnant or recently pregnant was a good idea.  And so we revised our standard death certificate – this is the standard that the states use to base their own state death certificates on –  we revised that to include this checkbox item.  So that was implemented in 2003 but only in a few states. Unfortunately, not all states implemented at the same time and so over the next, well, decade and a half – a little bit more than that actually – we had states implementing gradually this checkbox item and as a result that we saw increases in maternal mortality.  And it got to the point that in 2007, we decided that we couldn’t adequately interpret what was going on and so we stopped reporting maternal mortality altogether, waiting for all of the states to get onto the standard certificate at which point we planned to resume.  So the final state implemented the checkbox item in mid-year 2017, so 2018 is the first data year for which we have data from all states that is based on that checkbox.  So we decided we needed to do an evaluation though, of the data because research post 2003 showed that there were some problems with the checkbox – some errors that were evident.  And so we did this evaluation and we found indeed there were some problems and so we had to come up with a new method to code maternal mortality that would mitigate those errors.  So with the 2018 data we’re now releasing a figure that we believe reasonably represents the risk of maternal mortality in the United States.

HOST: Can we say that the maternal mortality deaths and the maternal mortality rate increased over time?

ROBERT ANDERSON: Well, we can’t really say that with any sort of certainty.  We do know that the increases that we’ve seen compared to the older data that we released, the increases that we’ve seen are largely – mostly even – due to implementation of the checkbox.  They don’t appear to be real increases.

ROBERT ANDERSON: We did an analysis based on 2015 and 2016 data.  The purpose of that particular analysis was to look at the effect of the checkbox on maternal mortality and what we found was that there was a dramatic increase in the number of maternal deaths detected as a result of using the checkbox.  And we also found that that increased very dramatically by age, so at the older ages, the checkbox increased the number of maternal deaths detected by quite a lot.

HOST: So the checkbox you feel then is giving a clearer picture of what the scope of the problem is?

ROBERT ANDERSON: I wish I could say that was the case – we feel like it is definitely allowing us to detect maternal deaths that we weren’t able to detect before.  That said, we know that there are some errors in the checkbox and we’re not entirely sure why these errors are occurring.  This is something that we’re going to be exploring over the course of the next year.  We’re trying to sort that out so we can actually correct it.  But the effect of these errors on the checkbox is that we are finding deaths to women who were not pregnant but for whom that the checkbox was checked that they were pregnant.  And some of these women are quite old actually – beyond reproductive age.

HOST: So when did you start uncovering those problems along this process?

ROBERT ANDERSON: Well, we didn’t actually discover this.  There were some states that were doing their own research on this – the state of Texas, for example, did some important research and they found errors.  CDC’s Division of Reproductive Health did some work with four states recently, that they recently published, that showed that this was the case as well.  And so we were really taking the results of that research, along with our own evaluation, to determine what was going on.

HOST: What else have you found – are there any geographic patterns that suggest maternal deaths are more prevalent in certain parts of the country?

ROBERT ANDERSON: Well, we can’t really say much about maternal mortality by state or by region. Unfortunately, we really don’t understand very well the variation in data quality from state to state. The numbers get quite small and it’s difficult to make judgments based on small numbers – the death rates, mortality rates, get to be very unstable with small numbers.

HOST: So some have been saying or arguing that the problem has been getting worse over time, that even now we don’t have a complete picture.  What would you say to that?

ROBERT ANDERSON: Well, I would agree that we don’t have a complete picture. The evidence that we’re seeing suggests that the problem isn’t really getting worse, but it doesn’t appear to be getting better either.  And that’s, uh, that’s something to be concerned about.  We have data from maternal mortality back to 1915 and we saw substantial declines – they’re really dramatic declines, we’ve seen dramatic decline since then and in recent decades the rate has been rather flat in comparison.

HOST: So one of these new reports looks at a 20 year period prior to the 2018 data. Could you talk about that?

ROBERT ANDERSON: Sure.  As part of our evaluation we did this initial study based on the 2015 and 2016 data to get a sense of the impact of the checkbox and that was based on actual data that we had, we recoded not using the checkbox and then compared it to what we had with the checkbox.  This other study was a little more involved and involves some statistical modeling, and so what we wanted to do with that study was to get a sense for what things would have looked like had all of the states implemented in 2003.  So that was the goal and so we have this trend based on these statistical modeling procedures that shows a fairly stable trend .

HOST: The second report was more focused on the years 2015 and 2016 – can you talk about that work?

ROBERT ANDERSON: Sure.  Yeah, the report based on the data years 2015 and 2016 is really an evaluation of the effect of the checkbox.  And those years were chosen because those were years for which we had data coded without the checkbox.  So we took these data, assuming no checkbox existed, and then we compared that with the data that we had that included the checkbox to get a sense for, to evaluate the effect of the checkbox on the maternal mortality.

HOST: Looking forward, are there any more initiatives underway in terms of improving this whole process and the quality of the data?

ROBERT ANDERSON: Yeah, there’s a lot of, a lot more work to do, really.  I mean, we have to understand better why these errors are occurring in the checkbox.  It may have something to do with electronic registration systems in the way they’re configured.  We’re not really sure, but what we really need to understand if we’re going to correct these errors – we really need to understand why they are occurring and so that’s something that we’ll be working on over the course of the next year.   In addition, we need to work with states and our plan is to do this, to work with states to investigate deaths to women of reproductive age to determine if a pregnancy or recent pregnancy was a factor in their death and this is this can be done using some data linkage to look in birth records and fetal death records for evidence of a pregnancy. I think we can glean a lot of information if we just, you know, take the time and effort to go and look and see.  What we have to do is, we have to work with the states to do this because they are the keeper of those records. They’re the ones that will have to do it and if we can support them in those efforts then hopefully we can get information that will feed back into the vital statistics system and provide us with better data in the future.

HOST: Robert Anderson, thank you for joining us.

New NCHS Reports Released This Week

January 21, 2022

NCHS Releases Latest NHIS Early Release Data

November 16, 2021

The Early Release (ER) Program of the National Health Interview Survey (NHIS) provides estimates, analytic reports, and preliminary microdata files on an expedited schedule. NHIS data users can have access to these very timely estimates, reports, and microdata files without having to wait for the release of the final annual NHIS microdata files by selected demographic characteristics.

One of the ER reports presents estimates of health insurance coverage for the civilian noninstitutionalized U.S. population based on data from the January through June 2021 National Health Interview Survey.

The ER program released preliminary estimates of the percentages of adults and children living in homes with only wireless telephones (also known as cellular telephones, cell phones, or mobile phones). These estimates are the most up-to-date estimates available from the federal government concerning the size and characteristics of this population.

ER also released quarterly and biannual health estimates on a variety of conditions.  The data is available on interactive web dashboards at the following links below:

Interactive Quarterly Estimates from the National Health Interview Survey, January 2019 – June 2021


Interactive Biannual Estimates from the National Health Interview Survey, January 2019 – June 2021


National Health Interview Survey Releases 7 New Early Release Products

August 31, 2021

The National Health Interview Survey Early Release Program has released 7 new products that include data on health insurance, key health indicators and wirless phone use.

The new products include a report that presents estimates of health insurance coverage for the civilian noninstitutionalized U.S. population based on data from the 2020 National Health Interview Survey.


Geographic Variation in Health Insurance Coverage: United States, 2019

August 6, 2021

NHSR162_Cover1NCHS releases a new report that presents state, regional, and national estimates of the percentage of persons who were uninsured, had private health insurance coverage, and had public health insurance coverage at the time of the interview.

Key Findings: 

  • In 2019, among persons under age 65, 12.0% were uninsured, 64.3% had private coverage, and 25.9% had public coverage at the time of the interview.
  • Among adults aged 18–64 (working-age adults), the percent uninsured ranged from 12.4% for those living in large fringe (suburban) metropolitan counties to 17.5% for those living in nonmetropolitan counties.
  • Working-age adults living in non-Medicaid expansion states (20.8%) were about twice as likely to be uninsured compared with those living in Medicaid expansion states (10.9%). Similar patterns were observed among children
    aged 0–17 years.
  • The percentage of working-age adults who were uninsured was significantly higher than the national average (14.5%) in Florida (20.6%), Georgia (22.3%), Oklahoma (25.6%), and Texas (30.5%), and significantly lower than the national average in California (11.5%), Minnesota (6.9%), New York (7.4%), Ohio (10.8%), Pennsylvania (9.8%), and Wisconsin (7.7%).
  • The percentage of people under age 65 who were uninsured was lowest in the New England region (4.6%).

Demographic Variation in Health Insurance Coverage: United States, 2019

June 29, 2021

New NCHS report presents national estimates of different types of health insurance coverage and lack of coverage (uninsured). Estimates are presented by selected sociodemographic characteristics, including age, sex, race and Hispanic origin, poverty status, education level, employment status, and marital status.


  • In 2019, 33.0 million (10.2%) persons of all ages were uninsured at the time of interview. This includes 32.5 million (12.0%) persons under age 65.
  • Among children, 3.7 million (5.1%) were uninsured, and among working-age adults (aged 18–64), 28.8 million (14.5%) were uninsured.
  • Among persons under age 65, 64.3% were covered by private health insurance including 56.5% with employment-based coverage and 6.5% with directly purchased coverage. Moreover, 4.0% were covered by exchange-based coverage, a type of directly purchased coverage.
  • Among persons under age 65, two in five children and one in five adults were covered by public health coverage, mainly by Medicaid and the Children’s Health Insurance Program (CHIP).
  • Among adults aged 65 and over, the percentage who were covered by private health insurance (with or without Medicare), Medicare Advantage, and traditional Medicare only varied by age, income level, education level, and race and Hispanic origin.

National Health Interview Survey Early Release Updates

February 11, 2021

The Early Release Program of the National Health Interview Survey (NHIS) publishes selected health estimates from an expedited schedule.

New Interactive quarterly and biannual early release estimates provide health statistics based on data from the 2019-June 2020 NHIS for selected health topics for adults aged 18 years and over.

New report on health insurance coverage provide detailed estimates from the 2019-June 2020 NHIS.  There are also health insurance quarterly web table estimates available for April–December 2019 and January–March 2020.

Wireless Substitution: Early Release of Estimates from the National Health Interview Survey, looks at household telephone status from January through June 2020.  This includes updated estimates of the size of the wireless-only and wireless-mostly population.

Reasons for Being Uninsured Among Adults Aged 18–64 in the United States, 2019

September 30, 2020

Questions for Amy Cha, Health Statistician and Lead Author of “Reasons for Being Uninsured Among Adults Aged 18–64 in the United States, 2019.”

Q: Why did you decide to do a report on this topic?

AC: In 2019, 14.5% of adults aged 18–64 were uninsured in the United States. Individuals without health insurance experience barriers to health care such as not having a usual source of care and postponing or forgoing care due to cost, which may lead to negative health outcomes. Therefore, in this report we evaluated the characteristics of uninsured adults aged 18–64 in 2019 and the percentage among uninsured adults who identified with six reasons for being currently uninsured.

Q: Was there a specific finding in the data that surprised you from this report?

AC: We were surprised that the percentage of adults who were uninsured due to cost was higher among women and adults in fair or poor health. The percentage who were uninsured due to cost increased with age from 66.8% among those aged 18–29 to 80.9% among those 50─64.

Q: How did you obtain this data for this report?

AC: The data for this report came from the 2019 National Health Interview Survey (NHIS) Sample Adult component. NHIS is a nationally representative, household survey of the civilian noninstitutionalized U.S. population. In 2019, the NHIS questionnaire was redesigned to better meet the needs of data users. The data is publicly available on the NHIS website (https://www.cdc.gov/nchs/nhis) with detailed data documentation.

Q: Is there any trend data for this report? If so, where can I find this data?

AC: We do not have any trend data for this report. With the NHIS redesign, questions concerning the reasons for being uninsured were asked in a different manner than in previous surveys and therefore are not comparable.

Q: What is the take home message for this report?

AC: Among uninsured adults aged 18–64, the most common reason for being currently uninsured was because they perceived that they could not afford the cost of coverage, followed by not being eligible, not wanting coverage, the process of signing up was too difficult or confusing, could not find a plan that meets their needs, and they signed up for coverage, but the plan has not started yet.